Psychology 202 - Test 2

Question 1

hypothesis testing

Answer 1

a statistical method that uses sample data to evaluate a hypothesis about a population

Question 2

hypothesis

Answer 2

the prediction about the relationship between two variables

Question 3

critical value

Answer 3

set cut-off sample score

Question 4

directional hypothesis

Answer 4

make a prediction regarding direction

i.e. increase…or decrease…

Question 5

one-tail test

Answer 5

looking at one tail/extreme of the distribution

• 5% > 1.64
• 1% > 2.33

Question 6

non-directional hypothesis

Answer 6

no prediction regarding direction

- just know there is a change, don’t know in/decrease

Question 7

two-tail test

Answer 7

need to look/think about both extremes

• 5% > 1.96
• 1% > 2.57

Question 8

distribution of means

Answer 8

set of sample means from a given population

Question 9

rule #1

Answer 9

the mean of a distribution of means (μm) is the same as the mean of the population of individuals

Question 10

rule #2a

Answer 10

The variance of the distribution of means is the variance of the population of individuals divided by the number of individuals in each sample

Question 11

rule #2b

Answer 11

the standard deviation of the distribution of means is the square root of the variance of the distribution of means

Question 12

rule #3

Answer 12

the shape of the distribution of means is approximately normal if at least one of the conditions is met

• sample size is 30 or more
• the distribution of the population of individual scores is normally distributed

Question 13

Variance & SD formulas for Distribution of Means

Answer 13

variance –> δ²m = δ² / N

SD –> √δ²m = δ² / N or √δ²m

Question 14

z-test

Answer 14

hypothesis testing procedure using the mean of the sample when the population variance is known
- comparing sample mean to distribution of means

Question 15

z-test formula

Answer 15

Z = (M - μm) / δ²

Question 16

statistical significance

Answer 16

the number is so extreme it is unlikely to have gotten it by chance

Question 17

Alpha (α) - Type I Error

Answer 17

• the null is true and the data tells us to reject

i. e. jury finding innocent man guilty

Question 18

Beta (β) - Type II Error

Answer 18

• the null is false and the data tells us to retain it

i. e. jury lets guilty man go free

Question 19

comparing studies

Answer 19

• as long as you have statistical significance, neither score is more than the other

Question 20

practical significance

Answer 20

difference meaningful in real-world context

- one leads to more improvement over other

Question 21

effect sizes

Answer 21

the extent to which population means differ and distributions overlap

Question 22

large effect size

Answer 22

little overlap with vastly different means

Question 23

small effect size

Answer 23

a lot of overlap with different but close means

Question 24

Cohen’s D

Answer 24

measure of effect size

• mean and how spread out the distribution is (SD/SE)
• allows us to examine practical significance (how different the groups are) and compare studies

Question 25

effect size cut-offs

Answer 25

small = .2
medium = .5
large = .8

Question 26

statistical power

Answer 26

the probability that a study will yield a statistically significant result if the research hypothesis is really true
- opposite is beta/type II error

Question 27

what affects power

Answer 27

• effect size
• sample size
• significance level (alpha)
• one vs. two tailed tests
• statistical test

Question 28

increase power

Answer 28

• more lenient cut-off (.05 over .01)
• increase sample size
• use one tail
• increase intensity of procedure
• be more precise > less diverse pop., standardized, controlled circumstances/more precise measurement